This question is about why I am getting strange results after running a
Hausman-McFadden test for the IIA assumption after multinomial logit
(-mlogit-) estimation.
I am estimating a McFadden choice model using -mlogit- with 8 choices and
about 1 million observations. The model is fully saturated (all my
right-hand-side variables are mutually-exclusive dummy variables). To test
the IIA assumption, I have run a Hausman-McFadden test:
1. I first conduct the estimation with all 8 choices, then save the
coefficient estimates (using -hausman, save-).
2. I re-estimate the model, but removing from the dataset all observations
that make a particular choice (it doesn't matter which one I remove). I
then test the equality of the coefficients versus the results of #1 above
(using -hausman, alleqs less-).
I am puzzled because all the coefficients from #2 are EXACTLY the same as
the coefficients from #1 above. (So of course, the chi-squared statistic on
the test is zero, with a p-value of 1.00.)
I am hesitant to interpret this result as saying that my model is PERFECTLY
specified. Rather, I suspect that some characteristic of my set-up (perhaps
the fact that the independent variables are mutually-exclusive dummies) is
generating this result, so that the test has no power in this situation.
Does anyone have any insight into what is going on?
Thanks in advance,
Dean
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Dean Yang
Ph.D. Candidate, Department of Economics
Littauer Center, Room 200
Harvard University
Cambridge, MA 02138
